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Corporate Information Factory, by William H. Inmon, Claudia Imhoff, Ryan Sousa
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- Sales Rank: #16730367 in Books
- Published on: 2002-02
- Format: Import
- Binding: Unbound
Most helpful customer reviews
11 of 12 people found the following review helpful.
50,000 ft-level architectural overview
By DTC#
I saw Ms. Imhoff give a talk, so I was motivated to buy her book. I was expecting more detail and more depth, but I was satisfied anyway. As a new comer to the data warehousing/OLAP field, I found it helpful to have a book that showed me the "forest"; many other books are available to show me the "trees."
The book is a very high-level architectural overview of the components of a "corporate information factory", including the data warehouse, data mart, and operational data store. It describes the components and their relationships. It describes the motivations and reasons these components are organized the way they are. It describes some of the important engineering tradeoffs in alternate designs.
The book is a quick and simple read. I got a few very important concepts and ideas from it, but I must definitely read several other books for greater depth and focus.
33 of 43 people found the following review helpful.
Inaccurate and pompous, with little substance
By Noone Inparticular
I approached this book with an open mind, but after I stumbled upon a couple of obviously wrong and some nonsensical statements, I started reading it much more skeptically, and finding more and more problems with it. (However, it did provide more fun ;))
The book has a good premise, trying to explain information system with the factory metaphor. Although authors give some good insight in the way IS should or could be thought of and modeled, there are many instances in the text where you read something and say to yourself "what where these good people thinking". This then undermines your confidence in their vision and full understanding of the matter. And although I think this is a matter of personal preference, authors sometimes seem to be in love with their style, producing some beautiful nonsense like this: "The legacy environment is only a very small vestige of its former invincible self." (pg. 42)
Let me give you some more examples of what I'm talking about:
Authors create metaphors of user classes, calling them "tourist, farmer, explorer and miner", which in itself is not a bad idea, but then they go on to say "...farmers found at the ODS environment are quite different from the farmers found at the data mart". So why did you create the single metaphor then?
Also, check this out: "A miner will typically look over many, many rows of data...". As opposed to what, just a "many rows of data"? Whence some people might need "not so many rows of data"? Like I'm reading a book for my eight-year-old, for goodness sakes!
Then there is this graph showing the directional flow of data, but then it reads: by the way, in all this streams, data can sometimes ("in 1-5% of the cases" - authors never say how they got these numbers, it is all a slight of hand) flow in the opposite direction!!?(Pg. 24) And they go about giving 5 examples, 4 of which are wrong - there is no data flow in them at all!
Example:"...sales dept. notes that loans are slowing down. The decision is made to reduce home loan rates by 1/2 percent."
This is not the back flow of data, as authors assert, it is an information feedback loop that involves people (management), and their decisions. Data (loan rates) is not coming back from Data Mart. User is somehow entering it into Operational system (application). His decision is influenced by data analysis, but it does not reverse the data flow. The fundamental issue here is that authors ignored the fact that information processes in the company involve people as well as the data and systems, and should be modeled as such. To use their metaphor, users should be a part of the information ecosystem. Hence it is not true that, as the book claims, corporate information factory embodies the information ecosystem. (Pg.7)
"...'event' date ...reflects the moment in time when the data in the record was accurate". (Pg. 96) This is incorrect. 'event' date is just recording the time of that single event. Record is always accurate after that, it does not 'age' with time.
At pg. 191 it is asserted that Data Warehouse provides "depth" to the data. That is true only if it is built (modeled) with "depth" requirements in mind. Before I can get "deep" information from the DW, I must build it with my questions in mind, otherwise, it will not give me data. An abstractly deep DW does not exist. It is always an answer to a particular question, or number of questions.
"The Dimension of History" (pg. 193-194) is just plain good old nonsense, with example (life stages of an individual) being completely off the mark. Reminds me of the student who does not know the correct answer to the question so he tries to invent some plausible response, letting his imagination fly ... Sad.
And so on, and so on...
I saved the best ones for the end:
"...the external world is full of normal occurrences and normal events. The very ordinary nature of the external world makes us take it for granted." (Pg. 49) Very philosophically deep, indeed ;)
"The emergence of the integrated applications comes slowly and, in many cases, imperceptibly" (pg.42) Yeah, it just creeps on you when you're not looking... ;)
".. the back flow of the data is minuscule to the point that in some cases it is so small as to be unmeasurable". (Pg. 23) :0 Beg your pardon? This is not quantum physics, guys, this is computer science. Anything can be observed, perceived and measured to the level of a single bit. Or are we talking bit-quarks here? Informational principle of uncertainty?
It is disappointing to have this book co-authored by the "father of the data warehouse".
To the (prospective) readers: This is a fun book if you are an experienced data architect, bad if you wish to use it as a blueprint for your work, and dangerous if you are an IT manager and impose it on your staff.
To the authors: Give us a break, please go back and re-make a decent book around the good basic idea. Less poetic style would also be appreciated. Forget about quantum physics. And give it to some unbiased reviewers first. Remember, only the real friends will tell you the unpopular truth.
11 of 13 people found the following review helpful.
Excellent starting point in data warehousing
By cityg
What a number of previous reviewers did not realise is that this book is about data warehouses, and not enterprise architecture, even though it is named to seem that way.
This book is an excellent high level overview of data warehouses and should be read by anyone who is going to be building a data warehouse from scratch or needs a starting place to learn about data warehouses. It explains all the concepts that are involved in building a data warehouse and explains what things can cause problems when implementing one.
It will not, however, describe the technical details on how to implement the data warehouse or many of the structures within it. That kind of information is readily available in many other books.
This is a perfect starting point for learning about data warehouses and especially good since it is a quick read and will not waste your time with a lot of wordiness.
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